In recent times, crowdsourcing has emerged as a convenient and economical method for organizations to outsource tasks, which require human involvement. The tasks are generally uploaded on a crowdsourcing platform, from where crowdworkers associated with the crowdsourcing platform may select the tasks. However, while performing such tasks, privacy has been a major concern. There may be a risk that the crowdworkers performing the tasks may access and subsequently misuse the private information available in the tasks. As an example, while performing a task that involves handwriting recognition in a medical form, crowdworkers may collect sufficient private information such as, but is not limited to, a name, an address, a phone number, an email address, a social security number, a patient ID, medicines use and so forth. Similarly, in another example, the crowdworkers performing the task of video labeling for traffic surveillance systems may collect the information pertaining to vehicle driver, vehicle type, location of vehicle etc. In view of the above, there remains a need for an efficient way to perform crowdsourcing tasks taking care of privacy concerns.